Diversity of molecular alterations, cellular compositions and clinical outcomes in cancer creates a major challenge in cancer treatment with respect to providing accurate diagnostic, prognostic, and predictive information. Tumors are typically described histopathologically using the tumor-node-metastasis (TNM) system. This system, which uses the size of the tumor, the presence or absence of tumor in regional lymph nodes, and the presence or absence of distant metastases, assigns a stage to the tumor as described by the American Joint Committee on Cancer (AJCC). The assigned stage is used as the basis for prognostication and for selection of appropriate therapy. However, this approach has many limitations. Tumors with similar TNM stage and histopathologic appearance can exhibit significant variability in terms of clinical course and response to therapy. For example, some tumors are very aggressive while others are not. Some tumors respond readily to hormonal therapy or chemotherapy while others are resistant.
The use of tumor biomarkers has provided an additional approach for dividing certain tumor types into subclasses. For example, one factor considered in prognosis and in treatment decisions for breast cancer is the presence or absence of the estrogen receptor (ER) in tumor samples. ER-positive breast cancers typically respond much more readily to hormonal therapies such as tamoxifen than ER-negative tumors. Though useful, this biomarker provides information for only a specific subset of breast cancers, leaving other subsets unaddressed.
Gene expression profiling has been successful in delineating specific breast cancer intrinsic molecular subtypes (Perou et al. 2000). This represents a significant advance in the understanding of breast cancer, the most commonly diagnosed cancer in women worldwide (Landis et al., 1999) and a disease that has proven to be quite heterogeneous in terms of its clinical presentation and features. Groups of breast cancer patients with distinct differences in their prognostic profiles have now been found to have equally distinct biologic and/or molecular profiles to help explain their associated clinical outcomes. This offers a tremendous opportunity to develop personalized therapeutics targeting the specific tumor biology associated with a specific molecular subtype of breast cancer. One particular molecular subtype that has garnered considerable interest is basal-like breast cancer (BLBC).
Although first reported more than 20 years ago on the basis of immunohistochemical (IHC) detection of basal cytokeratins (CK), this subtype again became notable after transcriptomic analysis of breast cancer confirmed its existence as a distinct molecular entity within breast cancer. While it differs substantially from the other delineated molecular subtypes in terms of its molecular makeup, the reason it has captured the attention of cancer biologists and clinicians alike is on account of its uniformly poor prognosis and lack of targeted therapy options. BLBC displays significant overlap with “triple-negative” breast cancer—a pathologic entity defined based on the absence of well-known breast cancer biomarkers estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor-2 (HER2). It is estimated that 60% to 90% of triple-negative breast cancers are BLBC. However BLBC is not synonymous with triple-negative breast cancer. Patients with BLBC are often younger, are more likely to be of African-American descent (Carey et al. 2006; Ihemelandu et al. 2007; Ihemelandu et al. 2008), are more likely to be BRCA1 mutation positive (Rakha et al. 2009), frequently develop distant metastatic disease to the brain and/or lung within 3-5 years of initial presentation (Wang et al. 2005) and have poor overall survival (Carey et al. 2006). In fact, the development of distant metastatic disease and subsequent death appears to be independent of initial presenting nodal status, as the majority of patients are lymph node negative at the time of initial diagnosis (Dent et al. 2007).
Currently the most effective biomarkers in routine clinical practice are theranostic biomarkers. Theranostic biomarkers provide information with respect to diagnosis (determination of the cancer biologic subtype), prognosis (determination of the clinical outcome) and therapeutic prediction (determination of therapeutic efficacy). Theranostic biomarkers are functionally most central and pivotal in the network of biomolecules that control the biology of their specific biologic subtype. Hence, targeted therapy directed towards a theranostic biomarker has a profound effect on clinical outcomes.
In breast cancer an example of a theranostic biomarker is ER. It accurately diagnoses “luminal” breast cancer patients (ER-positive), accurately prognosticates their outcome, and predicts their favorable response to tamoxifen, a drug that specifically targets ER. Prior to the introduction of tamoxifen therapy, ER-positive breast cancer patients had a poor prognosis. Their prognosis dramatically improved after therapy with tamoxifen became standard of care for such patients. Therefore, the most important component of a theranostic biomarker is the diagnosis it offers. Because with diagnosis comes prediction of therapeutic efficacy, which ultimately determines patient prognosis. While prognosis may change depending on advancements in therapy, the diagnosis of a biologic subtype, and therefore its target(s) for therapy will remain immutable. Moreover, the prognosis offered by a theranostic biomarker is more accurate than that offered by a non-theranostic biomarker. This is because theranostic biomarkers predict clinical outcomes that are very specific to the biology of the cancer subtype. For example, ER-positive status very specifically reflects the current favorable prognosis associated only with the luminal subtype because it takes into account subtype-specific treatment with anti-ER therapy (e.g. tamoxifen). Therefore, theranostic biomarkers offer superior prognosis.
Whole genome profiling technologies such as gene expression profiling (transcriptomics) have greatly expanded our knowledge of the genes and genetic pathways associated with the development and progression of cancer. Based on this knowledge, several commercialized multigene prognostic tests have entered the complex and expanding landscape of the cancer in vitro diagnostics (IVD) market. These tests contain many genes, only some of which indeed have critical functional importance to the survival and maintenance of the malignant phenotype. Such tests are unable to offer a refined understanding of the underlying biology of a specific subtype. In other words, the main drawback of such multigene prognostic tests is that they are not theranostic. They do not provide a diagnosis of a specific biologic subtype, and therefore they do not offer insight with regard to subtype-specific treatment. As a result, the prognostic value they offer is only an approximation across multiple subtypes. This is in contrast to a theranostic biomarker whose prognostic value is derived from a single subtype, and is therefore more precise and accurate.
Therefore the discovery and elucidation of theranostic biomarkers for BLBC and other cancers is important for the improvement of the classification of tumors and the treatment of cancer patients.